# Generative Ai

> Comprehensive resources on Generative AI, including a detailed roadmap, projects, use cases, interview preparation, and coding preparation.

- **Type:** MCP server
- **Install:** `agentstack add mcp-genieincodebottle-generative-ai`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [genieincodebottle](https://agentstack.voostack.com/s/genieincodebottle)
- **Installs:** 0
- **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [genieincodebottle](https://github.com/genieincodebottle)
- **Source:** https://github.com/genieincodebottle/generative-ai
- **Website:** https://aimlcompanion.ai/

## Install

```sh
agentstack add mcp-genieincodebottle-generative-ai
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

 
    
    
    
    
    

## 🎯 Learn AI/ML Interactively

I built **[AI-ML Companion](https://aimlcompanion.ai)** - every AI, ML, GenAI and Agentic AI concept covered here, taught visually with animated diagrams, quizzes, and hands-on Python.

**260+ modules • 20 tracks • 9 real-world projects • 11 tracks free to start**

[](https://aimlcompanion.ai)

Your go-to hub for end-to-end GenAI learning. ⭐ Star this repo to stay updated with the latest GenAI resources :)

## 📚 Table of Contents
- [Documentation & Learning Resources](#-documentation--learning-resources)
- [Practical Use Cases & Projects](#-practical-use-cases--projects)

---

## 📖 Documentation & Learning Resources

### 🎯 Getting Started
- **[GenAI Roadmap](./GenAI_Roadmap.md)** - Your complete learning path for GenAI
- **[AI/ML Roadmap](./docs/ai_ml_roadmap.pdf)** - Comprehensive AI/ML learning guide
- **[AI-ML Companion](https://aimlcompanion.ai/)** - Interactive AI/ML learning platform with 17 tracks, 250+ modules, visualizations, quizzes, and hands-on coding (ML fundamentals → LLMs → MLOps)
- **[Essential GenAI Terms](./docs/essential-terms-genai.pdf)** - Key terminology and concepts
- **[LLM Fundamentals](./docs/llm_fundamentals.pdf)** - Core concepts of Large Language Models

### 🧠 Core Concepts & Guides
- **[Vector Embeddings Guide](./docs/vector-embeddings-guide.pdf)** - Understanding vector representations
- **[Prompt Engineering](./docs/prompt_engineering.ipynb)** - Crafting effective prompts
- **[AI Patterns](./docs/ai-patterns.pdf)** - Top 25 AI design patterns
- **[ML Reference Guide](./docs/ml-reference-guide.pdf)** - Machine learning reference

### 🏗️ Architecture & Technical Stack
- **[GenAI Tech Stacks](./docs/genai-tech-stacks.pdf)** - Technology stack overview
- **[LLM Providers](./docs/llm_providers.pdf)** - Comparison of LLM providers
- **[Advanced RAG Decision Flow](./docs/advance-rag-decision-flow-chart.pdf)** - RAG architecture guide
- **[GenAI Project Lifecycle](./docs/genai-project-lifecycle.pdf)** - End-to-end project guide

### ☁️ Cloud Platform Guides
- **[GenAI on AWS](./docs/genai-with-aws-cloud.pdf)** - AWS implementation | [GitHub](https://github.com/genieincodebottle/rag-app-on-aws) | [YouTube](https://www.youtube.com/watch?v=x2P4Ee6PYNg)
- **[GenAI on Azure](./docs/genai-with-azure-cloud.pdf)** - Azure implementation guide
- **[GenAI on VertexAI](./docs/genai-with-vertexai.pdf)** - Google Cloud Vertex AI guide

### 💼 Career & Interview Preparation
- **[AI Scenario based Interview Q&A](https://aimlcompanion.ai/curriculum/interviewScenarios)** - ML/GenAI/Agentic AI Scenario based Interview Q&A
- **[GenAI Interview Q&A](./docs/genai-interview-questions.pdf)** - Common interview questions
- **[Agentic AI Interview Q&A](./docs/agentic-ai-interview-questions.pdf)** - Agent-specific interview prep
- **[90+ Multi-Agentic AI Interview Q&A](./docs/multi-agentic-interview-qna-latest.pdf)** - Multi-Agentic specific interview prep
- **[AI Roles & Important Topics](./docs/ai-roles-important-topics.pdf)** - Career paths and topics

### 🚀 Production & Enterprise
- **[GenAI Enterprise Production Checklist](./docs/genai_enterprise_prod_check_list.pdf)** - Production readiness guide

---

## 🛠️ Practical Use Cases & Projects

### 🔍 Retrieval-Augmented Generation (RAG)
- **[Advanced RAG](./genai-usecases/advance-rag/)** - Comprehensive RAG techniques including agentic, graph, multimodal, and 9 advanced patterns (corrective RAG, hybrid search, query expansion, etc.)
- **[Cache-Augmented Generation](./genai-usecases/cache_augmented_generation/)** - Alternative to RAG using context caching for faster responses

### 🤖 Agentic AI & Orchestration
- **[Agentic AI](./genai-usecases/agentic-ai/)** - Multi-agent systems with CrewAI & LangGraph frameworks
- **[AI Patterns](./genai-usecases/ai-patterns/)** - 25 advanced reasoning patterns (Chain-of-Thought, ReAct, Tree-of-Thought, Meta-Prompting, etc.)
- **[MCP - Model Context Protocol](./genai-usecases/mcp/)** - Standard protocol for LLM tool interoperability with web search
- **[Multi-Agentic Prod Grade Content Moderation System](./genai-usecases/content-moderation-system/)** - AI-Powered Multi-Agentic Content Moderation System with React Frontend
- **[Handling Latency in Multi-Agentic System](./docs/handling-latency-in-multi-agentic-systems.pdf)** - How to handle Latency in Multi-Agentic System 

### 💬 Conversational AI
- **[Chatbot with Memory](./genai-usecases/chatbot-with-memory/)** - PDF chatbot using local models with persistent conversation memory
- **[Conversational Analytics](./genai-usecases/conversational-analytics/)** - Full-stack app analyzing customer feedback (React + FastAPI + PostgreSQL)

### 🔧 LLM Providers & Tools
- **[LLM Providers](./genai-usecases/llm-providers/)** - Compare OpenAI, Gemini, Claude, Groq + local models (Ollama, HuggingFace)
- **[Embedding Models](./genai-usecases/embedding-models/)** - Guide to vector embeddings with Google, OpenAI, and HuggingFace

### 📊 Data & Analytics Applications
- **[Text-to-SQL](./genai-usecases/text-to-sql/)** - Convert natural language to SQL queries with visualization
- **[Graph Q&A](./genai-usecases/graph-qa/)** - Query Neo4j graph databases using natural language
- **[Sentiment Analysis](./genai-usecases/sentiment-analysis/)** - Analyze customer call transcripts for sentiment and aggressiveness
- **[Your AI Chat Analytics](./genai-usecases/your_ai_chat_analytics/)** - Chat analytics dashboard

### 🎨 Prompt Engineering & Security
- **[Prompt Engineering](./genai-usecases/prompt-engineering/)** - 16+ techniques from basics to APE (Automatic Prompt Engineer)
- **[Prompt Guard](./genai-usecases/prompt-guard/)** - Detect prompt injections and jailbreak attempts using Meta's Llama Guard

### 🖼️ Multimodal & Specialized
- **[Gemini Nano Banana](./genai-usecases/gemini-nano-banana/)** - Text-to-image generation with Gemini 2.5 Flash
- **[Llama 4 Multi-Function App](./genai-usecases/llama-4-multi-function-app/)** - All-in-one app: chat, OCR, RAG, and agentic AI

### ⚡ Automation
- **[n8n Automation](./genai-usecases/n8n-automation/)** - Setup and usage guide for n8n workflow automation platform

---

### 🔗 Quick Access Links
| Category | Resources |
|----------|-----------|
| **Learning Platform** | [AI-ML Companion](https://aimlcompanion.ai/) — Interactive AI/ML learning with 17 tracks, 250+ modules, quizzes & coding |
| **Learning Path** | [GenAI Roadmap](./GenAI_Roadmap.md) • [AI/ML Roadmap](./docs/ai_ml_roadmap.pdf) |
| **Fundamentals** | [Essential Terms](./docs/essential-terms-genai.pdf) • [LLM Fundamentals](./docs/llm_fundamentals.pdf) • [Embeddings Guide](./docs/vector-embeddings-guide.pdf) |
| **Cloud Platforms** | [AWS](./docs/genai-with-aws-cloud.pdf) • [Azure](./docs/genai-with-azure-cloud.pdf) • [VertexAI](./docs/genai-with-vertexai.pdf) |
| **Interview Prep** | [GenAI Q&A](./docs/genai-interview-questions.pdf) • [Agentic AI Q&A](./docs/agentic-ai-interview-questions.pdf) |
| **Popular Projects** | [Advanced RAG](./genai-usecases/advance-rag/) • [Agentic AI](./genai-usecases/agentic-ai/) • [Text-to-SQL](./genai-usecases/text-to-sql/) |

## 🤝 Contributing

Contributions are welcome. To add useful resources or code:

1. Fork this repo

2. Clone it
   ```
   git clone https://github.com/genieincodebottle/generative-ai.git
   ```
3. Create a branch
   ```
   git checkout -b feature-name
   ```
4. Make changes and commit
   ```
   git commit -m "Your message"
   ```
5. Push your branch
   ```
   git push origin feature-name
   ```
6. Open a Pull Request with a brief description of your changes.

## Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [genieincodebottle](https://github.com/genieincodebottle)
- **Source:** [genieincodebottle/generative-ai](https://github.com/genieincodebottle/generative-ai)
- **License:** MIT
- **Homepage:** https://aimlcompanion.ai/

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/mcp-genieincodebottle-generative-ai
- Seller: https://agentstack.voostack.com/s/genieincodebottle
- Browse the marketplace: https://agentstack.voostack.com/browse

---
Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.